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<dc:title xml:lang="en">Estimation of component temperatures of vegetative canopy with Vis</dc:title>
<dcterms:alternative xml:lang="fr">Estimation de la température des composants du couvert végétal à partir des données multidirectionnelles dans les domaines visible et infrarouge thermique par l inversion des modèles de transfert radiatif du couvert</dcterms:alternative>
<dc:subject xml:lang="fr">Géothermie</dc:subject>
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<tef:elementdEntree autoriteSource="Sudoc" autoriteExterne="027394239">Thermométrie</tef:elementdEntree>
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<dcterms:abstract xml:lang="fr">Surface temperature, that results from energy balance of atmosphere-terrain interactions, bring the information of the physics of land-surface processes and has been viewed as a key variable of the parameterizations of energy and mass cycle which is crucial for climatological, hydrological, ecological, biogeochemical and meteorological modeling in regional, continental and global scales. The separation of component temperature is the basic step for the application of two-source algorithm. Multi-angular thermal infrared measurements provide a chance for the estimation of component temperatures (namely, soil and vegetation temperatures) with remotely-sensed data. The objective of this study is to explore the factors that affect the estimation of component temperatures and propose new algorithm for inverting the canopy radiative transfer models to compute component temperatures. This thesis is composed with six chapters. Within first chapter, the background of the simulation of radiative transfer through vegetative canopy and the estimation of component temperatures is introduced. A review of previous studies is also presented in this chapter. The second chapter is devoted to the comparison of a number of leaf angle distribution functions, and the evaluation of the effects of leaf angle distribution function on extinction coe+-cient which is a key parameter for simulating the radiative transfer through vegetative canopy. The third chapter is to explore the capability of clumping index to represent the spatial heterogeneity and investigate the effects of spatial heterogeneity on the separation of component temperatures. The fourth chapter is to develop an analytical model to simulate the thermal radiative transfer through vegetative canopy with an emphasis on the hot spot effect. The fifth chapter is to invert the radiative transfer model with neural network to obtain component temperatures. The sixth chapter is to make conclusion with the basis of previous chapters.</dcterms:abstract>
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<tef:nom>Université de Strasbourg</tef:nom>
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<tef:nom>Wang</tef:nom>
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es</tef:thesis.degree.name>
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<tef:nom>Li</tef:nom>
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